The invention relates generally to radar receivers, and more specifically, it relates to a low rank approximation to interference covariance for target detection in non-Gaussian clutter.
This invention addresses the problem of signal detection in interference composed of clutter (and possibly jamming), having a covariance matrix with known structure but unknown level and background white noise. The technique developed in this paper ensures invariance with respect to the unknown level and the background noise power. The research is motivated by the problem of space-time adaptive processing (STAP) for airborne phased-array radar applications. Typically, a radar receiver front end consists of an array of J antenna elements processing N pulses in a coherent processing interval. We are interested in the problem of target detection given the JN×1 spatio-temporal data vector.
Patented art of interest includes the following U.S. Patents, the disclosures of which are incorporated herein by reference:
U.S. Pat. No. 6,771,723 entitled Normalized parametric adaptive matched filter receiver issued to Davis
U.S. Pat. No. 5,640,429 issued to Michels and Rangaswamy;
U.S. Pat. No. 5,272,698 issued to Champion;
U.S. Pat. No. 5,168,215 issued to Puzzo;
U.S. Pat. No. 4,855,932 issued to Cangiani; and
U.S. Pat. No. 6,266,321 issued to Michels, et al.
The Davis patent describes an apparatus and method for improving the detection of signals obscured by either correlated Gaussian or non-Gaussian noise plus additive white noise. Estimates from multichannel data of model parameters that described the noise disturbance correlation are obtained from data that contain signal-free data vectors, referred to as “secondary” or “reference” cell data. These parameters form the coefficients of a multichannel whitening filter. A data vector to be tested for the presence of a signal passes through the multichannel whitening filter. The filter output is then processed to form a test statistic.
Cangiani et al. disclose a three dimensional electro-optical tracker with a Kalman filter in which the target is modeled in space as the superposition of two Guassian ellipsoids projected onto an image plane. Puzzo offers a similar disclosure. Champion discloses a digital communication system.
Michels et al., U.S. Pat. No. 6,226,321, hereby incorporated by reference, discloses implementations, for a signal that has unknown amplitude. For the signal of unknown amplitude, Michels et al. teaches us how to incorporate the estimated signal amplitude directly into the parametric detection procedure. Furthermore, Michels teaches two separate methods, namely, (1) how to detect the signal in the presence of partially correlated non-Gaussian clutter disturbance and (2) how to detect the signal in the presence of partially correlated Gaussian clutter disturbance. Furthermore, the method to detect the signal in the presence of partially correlated non-Gaussian clutter involves processing the received radar data and requires the use of functional forms that depend upon the probability density function (pdf) of the disturbance. Thus, the latter method requires knowledge of the pdf statistics of the non-Gaussian disturbance. The method does not teach how to process the data in such a manner that would not require knowledge of the disturbance processes. Furthermore, it does not teach how to process the data with one method that would detect the signal in either Gaussian or non-Gaussian disturbance. Thus there exists a need for apparatus and method of processing the data with a detection method that does not require knowledge of the clutter statistics. Furthermore, there exists a need for a method that detects the signal in either Gaussian or non-Gaussian disturbance.
The performance improvements of the presently disclosed invention relative to prior art are detailed in J. H. Michels, M. Rangaswamy, and B. Himed, “Evaluation of the Normalized Parametric Adaptive Matched Filter STAP Test in Airborne Radar Clutter,” IEEE Internationals Radar 2000 Conference, May 7-11, 2000 Washington, D.C. and J. H. Michels, M. Rangaswamy, and B. Himed, “Performance of STAP Tests in Compound-Gaussian Clutter,” First IEEE Sensor Array and Multichannel Signal.
Previous efforts derived the normalized matched filter (NMF) test for the problem of detecting a rank one signal in additive clutter modeled as a spherically invariant random process. The NMF test is given by             Λ      NMF        =                            ❘                                                    e                H                            ⁢                              R                c                                  -                  1                                            ⁢              x                        ⁢                          ❘              2                                                            [                                          e                H                            ⁢                              R                c                                  -                  1                                            ⁢              e                        ]                    ⁡                      [                                          x                H                            ⁢                              R                c                                  -                  1                                            ⁢              x                        ]                              ⁢              ≷                  H          0                          H          1                    ⁢              λ        NMF              ,where x is the observed data vector, e is the known spatio-temporal signal steering vector, and Rc is the known clutter covariance matrix. A statistic similar in spirit was also considered in for vector subspace detection in compound-Gaussian clutter.